In a Sea of Tech Talent, Companies Can’t Find the Workers They Want

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.

Apple has dominated the electronics supply chain for years. No more.

Artificial-intelligence companies are writing huge checks for chips, memory, specialised glass fibre and more, and they have begun to out-duel Apple in the race to secure components.

Suppliers accustomed to catering to Apple’s every whim are gaining the leverage to demand that the iPhone maker pay more.

Apple’s normally generous profit margins will face pressure this year, analysts say, and consumers could eventually feel the hit.

Chief Executive Tim Cook mentioned the problem in a Thursday earnings call, saying Apple was seeing constraints in its chip supplies and that memory prices were increasing significantly.

Those comments appeared to weigh on Apple shares, which traded flat despite blowout iPhone sales and record company profit.

“Apple is getting squeezed for sure,” said Sravan Kundojjala, who analyses the industry for research firm SemiAnalysis.

AI chip leader Nvidia recently became the largest customer of Taiwan Semiconductor Manufacturing , or TSMC, Nvidia Chief Executive Jensen Huang said on a podcast.

Apple had been TSMC’s biggest customer by a wide margin for years. TSMC is the world’s leading manufacturer of advanced chips for AI servers, smartphones and other computing devices.

Spokesmen for Apple and TSMC declined to comment.

The big computers that handle AI tasks don’t look like the smartphones consumers own, but many companies supply components for both. In particular, memory chips are in short supply as companies such as OpenAI, Alphabet’s Google, Meta , Microsoft and others collectively spend hundreds of billions of dollars to build AI computing capacity.

“The rate of increase in the price of memory is unprecedented,” said Mike Howard , an analyst for research firm TechInsights.

That applies both to the flash memory chips that store photos and videos, called NAND, as well as the memory used to run apps quickly, called DRAM.

By the end of this year, the price of DRAM will quadruple from 2023 levels, and NAND will more than triple, estimates TechInsights.

Howard estimates that Apple could pay $57 more for the two types of memory that go into the base-model iPhone 18 due this fall compared with the base model iPhone 17 currently on sale. For a device that retails for $799, that would be a big hit to profit margins.

Apple’s purchasing power and expertise in designing advanced electronics long made it an unrivaled Goliath among the Asian companies that make most of the iPhone’s parts and assemble the device.

Apple spends billions of dollars a year on NAND, for instance, according to people familiar with the figures, likely making it the single biggest buyer globally. Suppliers flocked to win Apple’s business, hoping to leverage its know-how and prestige to attract other customers.

These days, however, “the companies now pushing the boundaries of human‑scale engineering are the ones like Nvidia,” said Ming-chi Kuo, an analyst with TF International Securities.

Demand for AI hardware is poised to keep growing rapidly. Apple’s spending growth is modest in comparison with what is being spent to fill up AI data centers, even though it is breaking records with huge sales of the iPhone 17.

Samsung Electronics and SK Hynix are raising the price of a type of DRAM chip for Apple, according to people familiar with Apple’s supply chain.

Big AI companies pay generously and are willing to lock in supply and make upfront payments, giving the South Korean chip makers leverage against the iPhone maker.

Apple signs long-term contracts for memory, but it has used its heft to squeeze suppliers.

Its contracts have empowered it to negotiate prices as often as weekly, and to even refuse to buy any memory from a supplier if Apple didn’t view the price as favorable, according to people familiar with its memory purchases.

To boost leverage with suppliers, Apple even began stocking more inventory of memory. That was atypical for Cook, who normally cuts inventory to the bone to maximize Apple’s cash flow.

Apple is fighting not only for current deliveries but also for the attention of engineers at suppliers.

Glass scientists who worked on developing the smoothest and lightest smartphone displays are now also spending time on specialised glass for packaging advanced AI processing chips, according to industry executives.

Makers of sensors and other gizmos inside the iPhone are winning new business from AI companies such as OpenAI that are developing their own hardware.

Still, suppliers said they were far from giving up on business with Apple. Working with Apple is a form of education, they said, because it remains one of the most demanding and disciplined customers in the industry.

TSMC, the Taiwanese chip manufacturer, has built successive generations of its most advanced chips with Apple as its lead customer, relying on the big predictable demand for iPhones.

Now that TSMC is doing more business with Nvidia and other AI companies, people with knowledge of the chip supply chain said Apple was exploring whether some lower-end processors could be made by someone other than TSMC.

One of Apple’s biggest profit-spinners is selling extra memory for far more than the memory chips cost the company.

Last fall Apple discontinued the iPhone Pro model with 128 gigabytes of storage.

Customers who want that model must now start at 256 gigabytes and pay $100 more—the type of move that could be repeated this year to help Apple offset higher costs, wrote Craig Moffett, an analyst at Moffett Nathanson, in an investor note.

However, Apple isn’t expected to raise the price of its next iPhone models over similarly equipped iPhone 17s, said Kuo, the analyst.

News Corp, owner of The Wall Street Journal, has a commercial agreement to supply news through Apple services.

In a Sea of Tech Talent, Companies Can’t Find the Workers They Want

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

Playing a different game

Overlooked

Parts for iPhones to cost more owing to surging demand from AI companies.